• Annual Conference of KIPS
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• 2015.04a
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• pp.212-213
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• 2015

Data aggregation is a fundamental problem in wireless sensor networks that has attracted great attention in recent years. On constructing a robust algorithm for minimizing data aggregation delay in wireless sensor networks, we consider limited transmission range sensors and approximate the minimum-delay data aggregation tree which can only be built in networks of unlimited transmission range sensors. The paper proposes an adaptive method that can be applied to maintain the network structure in case of a sensor node fails. The data aggregation tree built by the proposed scheme is therefore self-healing and robust. Intensive simulations are carried out and the results show that the scheme could adapt well to network topology changes compared with other approaches.

• Smart Structures and Systems
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• v.18 no.5
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• pp.885-909
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• 2016

Advances in low-cost wireless sensing have made instrumentation of large civil infrastructure systems with dense arrays of wireless sensors possible. A critical issue with regard to effective use of the information harvested from these sensors is synchronized sensing. Although a number of synchronization methods have been developed, most provide only clock synchronization. Synchronized sensing requires not only clock synchronization among wireless nodes, but also synchronization of the data. Existing synchronization protocols are generally limited to networks of modest size in which all sensor nodes are within a limited distance from a central base station. The scale of civil infrastructure is often too large to be covered by a single wireless sensor network. Multiple independent networks have been installed, and post-facto synchronization schemes have been developed and applied with some success. In this paper, we present a new approach to achieving synchronized sensing among multiple networks using the Pulse-Per-Second signals from low-cost GPS receivers. The method is implemented and verified on the Imote2 sensor platform using TinyOS to achieve $50{\mu}s$ synchronization accuracy of the measured data for multiple networks. These results demonstrate that the proposed approach is highly-scalable, realizing precise synchronized sensing that is necessary for effective structural health monitoring.

• Journal of Sensor Science and Technology
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• v.19 no.3
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• pp.184-190
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• 2010

In this paper, a remote submersion warning system based on multi-mode optical fiber(MMF) sensors and a wireless sensor network(WSN) are proposed. To improve the reliability and stability of the sensors, the dual optical fiber sensors combined to the optical coupler are demonstrated. A slave zigbee as a wireless sensor module was used as a platform to monitor and record the signal from the MMF sensors and then transmits these information to a master zigbee wirelessly. The monitoring system running the $LabVIEW^{(R)}$ software was connected to the internet to support the short message service(SMS) through extensible markup language(XML) web service. No matter where the managers are, they can always receive the real-time remote-monitoring data for safety check.

• Journal of KIISE
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• v.42 no.3
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• pp.399-407
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• 2015

Wireless sensor networks are used for data collection and processing from the surrounding environment for various applications. Since wireless sensor nodes operate on low computing power, restrictive battery capacity, and low network bandwidth, their architecture model has greatly affected the performance of applications. If applications have high computation complexity or require the real-time processing, the centralized architecture in wireless sensor networks have a delay in data processing. Otherwise, if applications only performed simple data collection for long period, the distributed architecture wasted battery energy in wireless sensors. In this paper, the energy consumption and processing delay were analyzed in centralized and distributed sensor networks. In addition, we proposed a new hybrid architecture for wireless sensor networks. According to the characteristic of applications, the proposed method had the optimal number of wireless sensors in wireless sensor networks.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.8 no.3
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• pp.116-121
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• 2009

A novel method for improving the reliability of sensing data using multi-sensors in wireless sensor network systems is presented in this paper. This method is successfully applied a fog monitoring system in the mountain area.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2640-2644
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• 2014

With the development of technology, wireless sensor networks (WSN) are wireless networks of consisting a large number of small and low-cost sensors. Wireless sensor networks facilitate collaboration to achieve the perception of information collection, processing and transmission tasks in deployment area. They have various purposes such as military, disaster relief, medical rescue, environmental monitoring, precision farming and manufacturing industry etc. Therefore, technologies for data maintaining technologies in sensor network environment is one of essential parts of sensor networks. In this paper, we present the essential particulars about data management technology at wireless sensor network environments and propound the issues. Further, we could organize and develop a systematic approach in solving the issues.

• International Journal of Contents
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• v.3 no.4
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• pp.1-7
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• 2007

There has been increased interest in wireless sensors in the last few years. This paper provides insight into the properties that make these sensors so attractive, specifically considering their efficiency, data reliability, and the ability to verify the data generated. Some advantages a wireless network presents over traditional information sensing are discussed as well. The paper considers how the environmental field can benefit from using these networks. Some of the possible challenges this industry will face in adopting this new method of data sampling and collection are also considered. A project we conducted raised concern over measures needed for the integrity of the communication system to be maintained, thus ensuring the integrity of the data being collected. From results of an experimental project conducted in York University, the reliability and usefulness of a sensor network is discussed.

• Journal of Korea Multimedia Society
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• v.13 no.11
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• pp.1657-1666
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• 2010

Underwater wireless sensor networks (UWSN) need stable efficient data transmission methods because of environmental characteristics such as limited energy resource, limited communication bandwidth, variable propagation delay and so on. In this paper, we explain an enhanced hybrid transmission method that uses a hexagon tessellation with an ideal cell size in a two-dimensional underwater wireless sensor network model (2D) that consists of fixed position sensors on the bottom of the ocean. We also propose an energy efficient sensing and communication coverage method for effective data transmission in a three-dimensional underwater wireless sensor network model (3D) that equips anchored sensors on the bottom of the ocean. Our simulation results show that proposed methods are more energy efficient than the existing methods for each model.

• Journal of IKEEE
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• v.11 no.4
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• pp.322-330
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• 2007

Recent advances in wireless networks and low-cost, low-power design have led to active research in large-scale networks of small, wireless, low power sensors and actuators, In large-scale networks, lots of timing-synchronization protocols already exist (such as NTP, GPS), In ad-hoc networks, especially wireless sensor networks, it is hard to synchronize all nodes in networks because it has no infrastructure. In addition, sensor nodes have low-power CPU (it cannot perform the complex computation), low batteries, and even they have to have active and inactive section by periods. Therefore, new approach to time synchronization is needed for wireless sensor networks, In this paper, I propose Energy-Efficient Time Synchronization (EETS) protocol providing network-wide time synchronization in wireless sensor networks, The algorithm is organized two phase, In first phase, I make a hierarchical tree with sensor nodes by broadcasting "Level Discovery" packet. In second phase, I synchronize them by exchanging time stamp packets, And I also consider send time, access time and propagation time. I have shown the performance of EETS comparing Timing-sync Protocol for Sensor Networks (TPSN) and Reference Broadcast Synchronization (RBS) about energy efficiency and time synchronization accuracy using NESLsim.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.2
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• pp.247-268
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• 2011

Due to the application-specific nature of wireless sensor networks, the sensitivity to such a requirement as data reporting interval varies according to the type of application. Such considerations require an application-specific, parameter tuning paradigm allowing us to maximize energy conservation prolonging the operational network lifetime. In this paper, we propose a reporting interval adaptive, sensor control platform for energy-saving data gathering in wireless sensor networks. The ultimate goal is to extend the network lifetime by providing sensors with high adaptability to application-dependent or time-varying, reporting interval requirements. The proposed sensor control platform is based upon a two phase clustering (TPC) scheme which constructs two types of links within each cluster - namely, direct link and relay link. The direct links are used for control and time-critical, sensed data forwarding while the relay links are used only for multi-hop data reporting. Sensors opportunistically use the energy-saving relay link depending on the user reporting, interval constraint. We present factors that should be considered in deciding the total number of relay links and how sensors are scheduled for sensed data forwarding within a cluster for a given reporting interval and link quality. Simulation and implementation studies demonstrate that the proposed sensor control platform can help individual sensors save a significant amount of energy in reporting data, particularly in dense sensor networks. Such saving can be realized by the adaptability of the sensor to the reporting interval requirements.